Overview\nA new diagnostic approach, named dSHERLOCK (digital SHERLOCK), has been developed to quickly and accurately quantify Candida auris (C. auris) strains and detect antimicrobial resistance (AMR) mutations. C. auris is a pathogenic yeast fungus that can cause severe infections in hospital and nursing home patients, especially those with compromised immune systems or invasive medical devices. It is known for its ability to spread easily, survive on surfaces, and develop resistance to standard disinfectants and antifungal medications.\n\n## Current Challenges\nExisting diagnostic methods for C. auris are often costly, slow, and require specialized equipment and personnel. They can take up to a week to identify the pathogen and its AMR profile, delaying crucial treatment for infected patients. Furthermore, current diagnostics often only detect a single C. auris strain in an all-or-nothing manner, failing to provide a comprehensive picture of mixed antifungal susceptibility within a sample.\n\n## The dSHERLOCK Solution\nThe dSHERLOCK system integrates the CRISPR-based SHERLOCK technology with ultra-sensitive single-molecule microarray technology and a machine learning-based artificial intelligence method. This combined approach allows for:\n* Rapid Detection and Quantification: Reliable detection of C. auris from swab samples within 20 minutes, and accurate quantification of fungal colonization within 40 minutes.\n* Antimicrobial Resistance (AMR) Identification: Pinpointing AMR-causing mutations, specifically against azole and echinocandin antifungal drugs, by monitoring distinct sequence-specific fluorescence signatures. This allows for the identification of multiple AMR profiles within a single patient sample.\n* Simplified Process: The assay has been streamlined into a "one-pot-reaction" for ease of use.\n\n## Development and Collaboration\nThe project was led by Wyss Institute Core Faculty members David Walt, Ph.D. and James Collins, Ph.D., with key contributions from Justin Rolando, Ph.D., Nicole Weckman, Ph.D., and Anton Thieme. Collaboration with the Wadsworth Center Mycology Lab at the New York State Department of Health, which provided initial patient samples, was crucial for validating the technology.\n\n## Future Implications\nThe dSHERLOCK platform is designed to meet major clinical requirements for a next-generation diagnostic. It offers the potential to prevent hospital-associated outbreaks and optimize treatment strategies for C. auris infections. The platform's adaptability also allows for its application to detect, quantify, and characterize other pathogens posing serious health problems.